Update app.py

app.py

@@ -56,10 +56,7 @@ nutritional_data = {
     }
 }
 
-def optimize_dishes_for_budget(city, daily_budget, weight):
-    # Calculate recommended daily protein intake
-    recommended_protein = 0.8 * weight
-
+def optimize_dishes_for_budget(city, daily_budget):
     # Extracting cost, calories, and protein data for the selected city
     costs = [nutritional_data[dish][city] for dish in nutritional_data]
     calories = [nutritional_data[dish]["Energy (kcal)"] for dish in nutritional_data]
@@ -68,18 +65,15 @@ def optimize_dishes_for_budget(city, daily_budget, weight):
     # Objective function: Maximize nutritional value (calories + protein)
     c = [-1 * (cal + prot) for cal, prot in zip(calories, proteins)]  # Minimize negative of nutrition for maximization
     
-    # Constraints: Total cost must not exceed the daily budget, and total protein must meet the recommended intake
+    # Constraint: Total cost must not exceed the daily budget
     A_ub = [costs]  # Sum of costs * portions <= daily_budget
     b_ub = [daily_budget]
     
-    A_eq = [proteins]  # Total protein must equal recommended intake
-    b_eq = [recommended_protein]
-
     # Bounds for each dish: minimum 1 portion
     bounds = [(1, None) for _ in costs]  # Minimum 1 portion for each dish
 
     # Solve the optimization problem
-    result = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq=b_eq, bounds=bounds, method='highs')
+    result = linprog(c, A_ub=A_ub, b_ub=b_ub, bounds=bounds, method='highs')
     
     if result.success:
         selected_dishes = []
@@ -108,7 +102,7 @@ def optimize_dishes_for_budget(city, daily_budget, weight):
         
         result_str += f"### Total Cost: ₹{total_cost:.2f}\n"
         result_str += f"### Total Calories: {total_calories:.2f} kcal\n"
-        result_str += f"### Total Protein: {total_protein:.2f} g (Recommended: {recommended_protein} g)\n"
+        result_str += f"### Total Protein: {total_protein:.2f} g\n"
         
         return result_str
     else:
@@ -137,9 +131,8 @@ def create_interface():
     with gr.Blocks() as demo:
         gr.Markdown("# Daily Budget Optimization for Best Nutrition")
         
-        # User inputs for city, weight, and daily budget
+        # User inputs for city and daily budget
         city_selector = gr.Dropdown(choices=cities, label="Select City")
-        weight_input = gr.Number(label="Your Weight (kg)", value=70)
         budget_input = gr.Number(label="Daily Budget (₹)", value=500)
         
         show_all_dishes_button = gr.Button("Show All Available Dishes")
@@ -153,13 +146,13 @@ def create_interface():
             return display_dishes_in_city(city)
         
         # Function to handle optimization
-        def run_optimization(city, daily_budget, weight):
-            return optimize_dishes_for_budget(city, daily_budget, weight)
+        def run_optimization(city, daily_budget):
+            return optimize_dishes_for_budget(city, daily_budget)
         
         show_all_dishes_button.click(fn=show_all_dishes, inputs=[city_selector], outputs=all_dishes_output)
-        optimize_button.click(fn=run_optimization, inputs=[city_selector, budget_input, weight_input], outputs=optimization_output)
+        optimize_button.click(fn=run_optimization, inputs=[city_selector, budget_input], outputs=optimization_output)
         
-        gr.Row([city_selector, weight_input, budget_input])
+        gr.Row([city_selector, budget_input])
         gr.Row(optimize_button)
         gr.Row(optimization_output)
         gr.Row(show_all_dishes_button)